Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference

@article{Gibson2020OrpheusAN,
  title={Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference},
  author={P. Gibson and Jos{\'e} Cano},
  journal={2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
  year={2020},
  pages={229-230}
}
  • P. Gibson, José Cano
  • Published 2020
  • Computer Science, Mathematics
  • 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
Optimising deep learning inference across edge devices and optimisation targets such as inference time, memory footprint and power consumption is a key challenge due to the ubiquity of neural networks. Today, production deep learning frameworks provide useful abstractions to aid machine learning engineers and systems researchers. However, in exchange they can suffer from compatibility challenges (especially on constrained platforms), inaccessible code complexity, or design choices that… Expand

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